An approach to predictive control of multivariable time-delayed plant: stability and design issues

Area of Science:

• Engineering
• Control Systems
• Automation

Background:

• Multivariable plants often present challenges in control due to complexity and time delays.
• Existing control methods may struggle with higher-order or non-minimal phase systems.
• Predictive control offers a potential framework for addressing these challenges.

Purpose of the Study:

• To present a new method for multivariable predictive control.
• To demonstrate the advantages of this predictive approach for handling time delays and complex plant dynamics.
• To develop and implement a compact and simple control algorithm for higher-order, non-minimal phase, and open-loop stable plants.

Main Methods:

• Development of a novel multivariable predictive control algorithm.
• Design and implementation of the control algorithm.
• Testing and validation on an air-conditioned system.
• Analysis of the control law's stability.

Main Results:

• The proposed multivariable predictive control method effectively handles plants with time delays.
• A compact and simple design is achieved for higher-order and non-minimal phase plants.
• The control algorithm was successfully implemented on an air-conditioned system.
• The stability of the developed control law was investigated.

Conclusions:

• The presented multivariable predictive control method offers a viable solution for complex industrial systems.
• The approach simplifies the control of plants with time delays and challenging dynamics.
• Further research can explore extensions to closed-loop unstable systems.